Prof. Preetesh Kantak is an Assistant Professor of Finance at the Kelley School of Business, Indiana University. His research interests include macrofinance, investments and alternative assets.
Industry Expertise (2)
Areas of Expertise (3)
University of North Carolina: Ph.D., Finance
University of North Carolina: M.B.A., Finance
Princeton University: B.S., Chemical Engineering
This paper studies how professional asset allocators such as endowments, fund-of-funds, or pension funds select fund managers for investments. We develop a simple model of their due diligence process to motivate predictions about the endogenous acquisition of private information and its effects on the timing of investment decisions. We test these predictions using a unique dataset with detailed information on the interactions between a large institutional investor and 1,093 hedge funds over the course of 8 years. We find that the amount of private information acquired during the meetings is strongly associated with a fund’s returns and risk. Furthermore, private information strongly influences the allocator’s decision to invest. A one-standard-deviation increase in our private information signal doubles the probability of fund selection and reduces the due-diligence time by 20%. Contrary to prior research, we find no evidence that relying on these subjective judgements is wasteful. Instead, in a matched sample, conditioned on fund characteristics and past performance, the 18-month average peer-adjusted returns are 1.5% higher for the selected funds.
Using a measure of local (i.e., metropolitan statistical area [MSA]) long-run growth prospects, I uncover a novel link between economic fundamentals and prices of a segmented asset class, housing. While excess housing returns are positively associated with the level of growth prospects, housing valuations (price-to-rent ratios) are negatively associated with shocks to growth prospects. I document a possible explanation for this in MSA-level consumption data: housing consumption is asymmetrically exposed to growth prospects in that it expands more quickly when prospects are strong than it contracts when prospects are poor. I then replicate and empirically investigate related return and valuation regressions using an asset pricing model that combines a persistent component in consumption, Epstein and Zin (1989) preferences, and nonseparable housing services and nonhousing consumption.
We establish that the labor market helps discipline asset managers via the impact of fund liquidations on their careers. Using hand-collected data on 1,948 professionals, we find that top managers working for funds liquidated after persistently poor relative performance suffer demotion entailing a yearly average compensation loss of $664,000. Scarring effects are absent when liquidations are preceded by normal performance or involve mid-level employees. Based on a model with moral hazard and adverse selection, we find that these results can be ascribed to reputation loss rather than bad luck. The findings suggest that performance-induced liquidations supplement compensation-based incentives.
This study is the second update of the original 2004 CMEF study, Characteristics of Equity Investment in Microfinance and seeks to illustrate the changes in growth, expansion and maturity of the commercial microfinance industry between 2005 and 2008. Note that data spreadsheets have not been annexed to the study, but are available upon request. The study quantifies the explosive organic growth, in terms of equity, assets, number of borrowers and depositors in the industry. This growth has been particularly vibrant in Asia. It further highlights structural changes in the industry. First, there is a general trend of mean reversion of leverage. That is, as the industry matures, higher levered regions are deleveraging versus lower levered regions. Second, there is evidence that greater financial intermediation is taking place. Microfinance Institutions (MFIs), especially in the African region, are clearly using deposits as a way to fund their loans. Third, using the Herfindahl equation, we were able to see concentration effects, particular in high growth regions such as India and Africa. This has clear impacts on competition and ultimately on the interest rates charged. Fourth, we developed an alternative risk ratio to better illustrate the effectiveness with which MFIs are managing their portfolio risk. We see that although Africa has traditionally had the highest PAR-30 ratios, African MFIs are managing their risk prudently from a historical perspective.
Asia fares much worse with this kind of metric. Fifth, we do a simple Dupont breakdown of return on equity (ROE) in order to ascertain the main drivers of profitability between 2005 and 2008. Profit margin determined the greatest percentage of variability in return on equity between MFIs. This dependence has clear implications in terms of what type of investor will succeed in the MFI industry. Finally, we present an update on the ownership structure of characteristic MFIs. We see evidence of acceleration in transformations, an increased willingness of local capital to fund MFIs, and a continued effort by NGOs to divest their original holdings.